Establishment of Risk Decision Model for Motorcycle Riding Space Control
Date Issued
2016
Date
2016
Author(s)
Chang, Che-Ning
Abstract
According to the statistics of the ministry of transportation and communications, the sharing rate of the motorcycle is 64% in 2015. However, in generally, the three-lane section’s inside lane is set to be “Forbidding-Motorcycles”. In order to protect the riding space of motorcycles, the government gradually cancelled the forbidding-motorcycles of the third lane based on the local conditions. Nevertheless, there is no detailed analysis of before and after of cancel the forbidding-motorcycles of the third lane. In this case, this study aims to find the influence of motorcycle policy in the safety of traffic measure. The study collects the accident data of forbidding-motorcycles of the third lane from 2011 to 2016 in Taipei. Using the Full Bayesian Method to build two Bayesian Statistical Models: Hierarchical Poisson-Gamma model and Hierarchical Poisson-Lognormal model. With the above models, the accident factors of each lane can be obtained. The DIC value can be applied to define the fitness degree of the model. The result shows that Hierarchical Poisson-Gamma model has better performance. Finally, analyzing the traffic characteristic and accident data which before and after the forbidding-motorcycles, and computing the risk of each road. This result is used in the CART to fine the difference of traffic situation because of the motorcycle policy. After setting the result to be the decision variable of CART, and the road geometric characteristics and traffic volume as the independent variable, the seven rules are gained. The random forests can be applied to find the key variables. Comparison of decision trees which construct by all factors, Bayesian factors and random forests factors. The results show the error is 19% of decision trees which construct by all factors, Bayesian factors and random forests factors, which is comparatively low. This CART can be the effecttive reference for the government to decide whether the forbidding-motorcycles policy of the third lane cancelled or not.
Subjects
Forbidding-Motorcycles Policy
Before and After Influence Analysis
Accidental Factor Analysis
Bayesian statistical model
Data Mining
Type
thesis